48 results about "Language disorder" patented technology

The invention relates to the technical field of medical information, and particularly provides a multi-modal Alzheimer's disease early screening algorithm based on a large language model. The algorithm first collects voice data and demographic information of participants. Voice data is processed through noise suppression, voice enhancement and speaker separation and is transcribed into a description text. An eGeMAPS feature set is extracted from the voice data and is subjected to time sequence splicing, and a multi-modal feature matrix is formed in combination with demographic information; the attention pooling module is used for obtaining key features, a support vector machine is used for feature classification, and potential Alzheimer's disease patients and healthy individuals are distinguished. And inputting the classification result, the description text and the demographic information into a large language model, deeply analyzing four language barriers by adopting a zero sample thinking chain: information content reduction, vocabulary semantic defects, poor reference continuity and psychological state language deficiency, and finally generating a comprehensive screening report. According to the algorithm, the accuracy of early diagnosis is improved by combining audio and semantic features.

The invention relates to the technical field of language barrier evaluation, and discloses a deep learning-based language barrier executive intervention effect evaluation method. The method comprises the following steps: acquiring real-time voice data and facial expression data of a language barrier patient in intervention training through a multi-modal data acquisition device to form an original behavior feature set; performing acoustic feature hierarchical analysis on the voice data by adopting a time sequence feature extraction network to generate a voice time sequence feature vector; performing micro-expression dynamic capture on the expression data through a three-dimensional convolutional neural network to generate an expression state feature vector; inputting the two types of vectors into a multi-modal feature fusion layer to carry out cross-modal correlation analysis, and generating a comprehensive behavior evaluation matrix; on the basis of the matrix, an intervention effect analysis model driven by an attention mechanism is adopted, a behavior improvement degree index of the current intervention stage is calculated, accurate evaluation of the intervention effect is achieved, and support is provided for dynamic adjustment of language barrier rehabilitation intervention.

To provide a system and method for providing speech instructions based on classification of speech of language communication from a user.SOLUTION: A computing system can generate speech characteristics of a first verbal communication using a first audio sample from a user. The computing system can determine a first speech classification of the first verbal communication based on the speech characteristics from a plurality of speech classifications. The computing system can select one action from a plurality of actions that includes modifying one or more speech characteristics that define a user's speech based on the first speech classification. The computing system can provide instructions to present a message prompting the user to perform the speech defined by this one action selected from the plurality of actions. The efficacy of the medication that the user is taking to address the condition can be increased.SELECTED DRAWING: Figure 1

The invention discloses a text data enhancement method based on government affair text language disease error correction, which comprises the following steps: constructing a proper noun and terminology dictionary, and recording the positions and types of proper noun and terminology; analyzing a syntactic structure and literary and physical characteristics according to a proper noun and terminology dictionary, and constructing a language disease generation rule; the method further comprises the following steps: preprocessing the to-be-processed text data to obtain a preprocessed text; the preprocessed text is translated back, wherein the preprocessed text is translated into a text of a target language, and then the text of the target language is translated back to an original language; comparing the texts before and after the back translation, and screening out new texts of which semanteme is not damaged and which have language diseases as enhanced data; generating a negative sample on the basis of the enhanced data by using a language disease generation rule, and expanding the negative sample as an unprocessed negative sample; the editing distance of the unprocessed negative samples is calculated, and texts with the editing distance smaller than a threshold value are reserved to serve as the finally generated negative samples.

A method for treating a language disorder in a patient includes receiving therapist input specifying a speech target and engagement indicator priority, capturing audio of a speech response to a therapy prompt, and identifying the language of the response using a multilingual language identification model. The method further comprises analyzing the speech response with a language-specific recognition model to extract speech features and classify errors across multiple linguistic and acoustic dimensions. Engagement indicators are extracted and used to compute an engagement score, which, along with the error classifications and speech target, informs a decision model that selects a therapy task. The selected task is presented to the patient, and a subsequent speech response is captured to update error classifications. The decision model is iteratively refined based on therapist input and revised error data, enabling adaptive, personalized therapy progression.

The invention discloses a wake-up method based on expression recognition, a robot and an interaction device capable of performing wake-up control through facial expressions of a user. The wake-up method and the robot are suitable for scenes such as psychological care, accompanying robots, child / old-age auxiliary equipment and the like. The device has multi-modal fusion perception and facial emotion active recognition awakening capability, and can remarkably improve the awakening accuracy, the humanization degree and the technical depth. By integrating an expression recognition awakening mechanism, the naturalness and initiative of man-machine interaction are improved, and the limitation of awakening depending on a single mode such as voice and touch control in the prior art is improved. The robot supports voice wake-up, touch wake-up and button wake-up modes at the same time, and a multi-mode fusion wake-up mechanism is achieved. The naturalness and usability of the psychological support robot in the man-machine interaction process are improved, and the psychological support robot is particularly suitable for non-contact emotion accompanying and psychological intervention of children, old people and language barrier users.

The invention relates to the technical field of computer software, and particularly discloses a brain voice evaluation method and system based on a DSM-V cognitive domain, and the method comprises the steps: obtaining the voice information of a user; feature extraction is carried out on the voice information based on a DSM-V cognitive domain to obtain spoken language feature information, and the spoken language feature information comprises vocabulary reaction feature information, vocabulary semantic feature information and vocabulary association feature information; according to the vocabulary reaction feature information, obtaining multiple stages of vocabulary feature information, and according to all the stages of vocabulary feature information, obtaining a vocabulary reaction feature evaluation value; and obtaining feature information of a plurality of vocabulary nodes according to the vocabulary semantic feature information. According to the method, a foundation is laid for comprehensive assessment by obtaining the voice information, multi-dimensional spoken language feature information is extracted based on the DSM-V cognitive domain, the brain voice function can be deeply analyzed, the problem that traditional assessment dimensions are single is solved, and for example, the root of the problem can be accurately positioned in language disorder diagnosis.

To provide a system that supports effective communication for those with language disorder by utilizing gestures and objects.SOLUTION: A system comprises a capturing unit, an analysis unit, a presentation unit, and a conversion unit. The capturing unit captures the user's gestures or objects. The analysis unit analyzes the video captured by the capturing unit. The presentation unit presents candidates based on the analyzed result. The conversion unit converts the candidates presented by the presentation unit into images, illustrations, or comics.SELECTED DRAWING: Figure 1

The application relates to the technical field of medical information, and specifically discloses a multi-modal Alzheimer's disease early screening algorithm based on a large language model. The algorithm first collects speech data and demographic information of participants. The speech data is processed through noise suppression, voice enhancement and speaker separation, and is transcribed into descriptive text. Then, the eGeMAPS feature set is extracted from the speech data and time-series spliced, and combined with the demographic information to form a multi-modal feature matrix. Key features are obtained using an attention pooling module, and feature classification is performed using a support vector machine to distinguish potential Alzheimer's disease patients from healthy individuals. The classification results, descriptive text and demographic information are input into the large language model, and zero-shot thinking chains are used to analyze four language barriers: reduced information content, lexical semantic defects, poor referential coherence and language loss of psychological state, and a comprehensive screening report is finally generated. The algorithm improves the accuracy of early diagnosis by combining audio and semantic features.

To provide a system capable of overcoming a linguistic barrier and allowing people around the globe to converse.SOLUTION: Provided is a system comprising: means for transcribing a conversation in association with a voice tool; means for interpreting the transcription into languages around the globe using a Chat GPT; and means for reproducing the interpreted transcription using the voice tool.SELECTED DRAWING: Figure 1

1. The name of the product of this design: Children's articulation rehabilitation device. 2. Purpose of the product of this design: Articulation rehabilitation equipment used to improve children's language ability and improve children's language disorders. 3. The design key point of this appearance design product lies in the shape. 4. The picture or photo that best illustrates the design points: Stereoscopic diagram 1.

The present invention provides a method and apparatus for generating speech synthesis information, which relates to the technical field of speech data processing and can be used in the financial field or other technical fields. The method includes: obtaining a target video, and extracting human joint point features and lip language features according to the target video; the target video includes real-time images of customers with speech disorders; fusing the human joint point features and the lip language features to obtain a fused feature, and performing text recognition on the fused feature to obtain text vocabulary information; performing speech synthesis on the text vocabulary information to obtain speech synthesis information. The apparatus executes the above method. The method and apparatus for generating speech synthesis information provided by the embodiments of the present invention can accurately and efficiently identify the speech information that customers with speech disorders want to express, and improve the business handling efficiency.

The invention belongs to the field of intelligent medical rehabilitation engineering, particularly relates to a speech recognition-based speech disorder adjuvant therapy system, and solves the problems of high pathological speech misjudgment rate, large dialect interference and single feedback in the prior art. A phoneme fault-tolerant threshold value is dynamically adjusted by constructing an adaptive speech recognition engine, regional features and pathological features are separated by using a dialect adaptation module, and three-dimensional simulation, AR real-time correction and touch graded vibration of vocal organs are realized in combination with a multi-modal feedback device; the pathological speech recognition precision is improved; and the neural remodeling efficiency is optimized.

The invention discloses a big language model security test method and system based on a small language cross-language attack. The method comprises the steps of constructing a small language selection strategy library, designing a cross-language semantic conversion engine, constructing a multi-dimensional language barrier, implementing a self-adaptive language switching mechanism and establishing a cross-language security evaluation system. According to the method, through dual language barriers of minority language input and Chinese output, a traditional single-language security detection system is effectively bypassed, attack content is presented in a minority language form, but a target model is forced to reply with Chinese, and a language understanding gap is established between input and output; the dynamic language switching strategy realizes intelligent cross-language attack, and the attack method can be adjusted in real time according to the defense response of the target model. According to the method, the adaptability, the concealment and the overall test effect of attacks are remarkably improved, and a systematized and efficient technical means is provided for large model security assessment in a multi-language environment.

The application relates to a development language disorder early identification method and system fusing neural activity features and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring original neurophysiological signals and matched clinical information, and constructing a data set; power features and coherence features of the signals are normalized to generate enhanced feature vectors; attention weighted feature vectors are obtained through mutual information based attention mechanism weighting; the radial basis function is used to nonlinearly map the feature vectors to a high-dimensional space to obtain extended feature vectors; a development language disorder early identification model is constructed, brain region level feature aggregation and modulation, clinical factor fusion and gate modulation are adopted, a decision function fusing nonlinear interaction items is introduced, and a binary cross entropy loss function is used to optimize the model; after model training is completed by using a training set, signals of a subject to be evaluated are input into the model after the same preprocessing, and an identification result is output. The application can improve the accuracy of development language disorder early identification.

According to an embodiment, a device for script extraction and subtitle transmission synchronized with live performing art content is provided. When a viewer views verbal performing arts such as plays or musicals, the device projects commentary subtitles synchronized in real time with performance content in a preferred language in front of eyes by using a display device including AR smart subtitle glasses, in order to eliminate a language barrier due to nationality or an auditory barrier caused by hearing impairment or hearing loss and enable viewing of the performing arts, so that the subtitles can be viewed in synchronization with the performance.

The invention discloses an adaptive bilingual scientific education content intelligent recommendation system, which belongs to the technical field of intelligent education recommendation systems, is particularly suitable for primary school multi-language background students, and comprises a learner model construction engine, a multi-language resource matching module, a learning path optimization module, a content difficulty adjustment module and a teacher support module. The scientific concept understanding degree and the language proficiency degree of students are subjected to two-dimensional modeling, the bilingual content proportion is dynamically adjusted based on a language ability self-adaptive weighting strategy, scientific knowledge acquisition and language ability development goals are collaboratively optimized, a personalized bilingual learning path is generated, and actual deployment shows that the system enables the scientific score to be improved by 32%, the English vocabulary amount to be increased by 45% and the learning efficiency to be improved by 30%. The influence of language barriers on scientific learning is effectively solved, and the dual purposes of scientific education and language education are achieved.

The utility model discloses a portable writing board for language barrier treatment, which belongs to the technical field of portable writing boards for language barrier treatment and comprises a supporting bottom frame, a mounting box is mounted at the upper end of the supporting bottom frame, a loudspeaker box is mounted on the side edge of the upper end of the supporting bottom frame, and an adjusting motor is mounted on one side of the inside of the supporting bottom frame. According to the multifunctional writing board, the writing board erasing mechanism is arranged, writing on the writing board can be erased conveniently through the writing board erasing mechanism, and therefore the writing board can be recycled conveniently, and the problem that the effect of erasing the writing board through an eraser is poor at present is solved; according to the blackboard eraser, the water outlet mechanism is arranged, and water in the erasing plate can flow out from the water outlet holes by pulling the adjusting plate, so that the sponge erasing pad is soaked, the erasing effect of the erasing plate on the writing board is improved, and the practicability of the blackboard eraser is improved.

1. Name of the product in this design: Speech Communication Assistive Training Device. 2. Purpose of this design: To provide speech training or assist communication for people with language impairments. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The invention discloses a limb hemiplegia language barrier interaction robot. The pronunciation is carried out, corresponding words are found, an adjacent pronunciation relation is established, words with similar pronunciation are found, and therefore the situation that a user wants to say one word but the pronunciation is fuzzy is prevented. The characters are matched, and the situation that the user is weak in pronunciation or swallowing the pronunciation due to body reasons is prevented by predicting the blank pause characters, so that the missing part of a section of speech is predicted. And repeatedly speaking words are skipped according to the repeated word recognition network. According to the repeated word recognition network, parameters in a threshold structure are modified, so that one repeated word recognition network is trained, and the purpose of equivalently setting networks with different structures is achieved by keeping parameters on different networks. And a better matching mode of the statement is judged by skipping the characteristics of the input neural network of the repeated words and predicting. Therefore, the technical effect of more accurately predicting the voice of the user with the hemiplegic limbs and the language is achieved.

To remove the language barrier between a person with hearing disabilities and a listener, and allow the person with hearing disabilities wearing gloves to communicate in sign language which is to be converted into voice or characters in real time, thereby realizing smooth interaction.SOLUTION: A glove sign language voice system includes: sign language recognition means for reading, by a sensor, hand gestures and facial expressions of a person with hearing disabilities who is wearing gloves, and converting them into voice or characters in real time; sign language analysis means for performing accurate sign language recognition and expression analysis utilizing sign language data and AI technology; and voice output means for realizing smooth interaction between the person with hearing disabilities and the listener.SELECTED DRAWING: Figure 1

The invention relates to a neural activity feature fused developmental language disorder early recognition method and system, and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring an original neurophysiological signal and matched clinical information, and constructing a data set; performing normalization processing on the power feature and the coherence feature of the signal to generate an enhanced feature vector; obtaining an attention weighted feature vector through attention mechanism weighting based on mutual information; performing nonlinear mapping to a high-dimensional space by using a radial basis function to obtain an extended feature vector; the method comprises the following steps: constructing a developmental language disorder early recognition model, introducing a decision function fused with a nonlinear interaction item by adopting brain region level feature aggregation and modulation, clinical factor fusion and gating modulation, and optimizing the model by a binary cross entropy loss function; and after model training is completed by using the training set, inputting a to-be-evaluated tested signal into the model after same preprocessing, and outputting an identification result. According to the invention, the accuracy of early recognition of the developmental language barrier can be improved.

1. The name of this design product: Language Disorder Assessment and Rehabilitation System. 2. Purpose of the product of this design: to be used for testing and training the language cognitive ability of patients with speech disorders. 3. The design key point of this appearance design product lies in the shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

A method, server, and computer-readable medium for detecting cognitive and language disorders. A computer-implemented method for assessing the presence of a condition in a subject is provided, the method comprising: generating facial landmarks on a received input video to define points associated with regions of interest on the subject's face; defining speech periods based on respective positions of the defined landmarks; measuring pause frequency, repetition patterns, and lexical variation during the speech periods without determining or applying semantic information associated with the speech to generate an overall score; and generating a prediction of the presence of the condition in the subject, associated with the overall score, based on the overall score.

The invention discloses a language disorder assessment method and system, and belongs to the technical field of data processing, and the method comprises the steps that a user side accesses a language assessment platform, a language cognition task is generated, the language cognition task comprises a main language task and a secondary cognition task, and task sequence generation is carried out with cognition load increase; issuing the language cognition task to a user side thread, executing a task language test, and returning a task language flow; and a cognitive evaluation module embedded in the language evaluation platform is triggered, cascade evaluation based on logic paradox, language entropy change and a high-dimensional semantic network is executed, a language evaluation result is generated, and popup window display is performed on a platform user side. According to the method and the device, the technical problem that potential or slight language barriers are difficult to effectively induce and detect due to single language evaluation environment and lack of cognitive pressure in the prior art is solved.

Pharmacological methods and single unit dosage forms for treating the expressive language deficit in an autistic human child or adult are provided. A therapeutically effective dose of enantiomerically enriched R-ethosuximide or a pharmaceutically acceptable salt thereof is administered to a patient suffering from expressive language deficit, preferably over an extended period, e.g., six months or longer, to reduce the autistic patient's expressive language deficit.

The invention discloses a psychological health coach voice model optimization method based on large language model driving, and the method employs a voice signal preprocessing module, a multi-modal emotion feature extraction module, a dynamic weight distribution module, a large language model reasoning module, a voice synthesis optimization module, and a hardware cooperation acceleration module which are sequentially connected in series through a data bus. The dynamic weight distribution module is in two-way communication with the multi-modal emotion feature extraction module and the large language model reasoning module, and the hardware collaborative acceleration module is in parallel connection with the large language model reasoning module through a PCIe channel; according to the invention, through the multi-modal feature fusion (voice, text and micro-expression) and dynamic weight distribution technology, the emotion recognition precision is obviously improved, and the complex emotion state of a user is effectively captured; the dialect self-adaption unit breaks through regional language barriers through accent conversion mapping, and the dialect user interaction effectiveness is improved.

1. The name of the design product: language development disorder brain magnetic diagnostic instrument. 2. The use of the design product: application instrument for diagnosing autism and other language disorder children. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view. 5. The bottom of the design product is not easy to see or not visible during use, omit the top view.

To overcome the barrier of languages, automatically translate speech of the other person into the native language of the user, and provide an answer.SOLUTION: A system for overcoming the barrier of languages includes means for automatically translating speech of the other person into the native language of a user; and supporting an answer on the basis of the translated speech.SELECTED DRAWING: Figure 1